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Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity

North American Chapter of the Association for Computational Linguistics
Retrieval-Augmented Large Language Models (LLMs), which incorporate the non-parametric knowledge from external knowledge bases into LLMs, have emerged as a promising approach to enhancing response accuracy in several tasks, such as Question-Answering (QA)
Soyeong Jeong   +4 more
semanticscholar   +1 more source

Proof Complexity Generators

Algorithms and Complexity in Durham
The P vs. NP problem is one of the fundamental problems of mathematics. It asks whether propositional tautologies can be recognized by a polynomial-time algorithm. The problem would be solved in the negative if one could show that there are propositional
J. Krajícek
semanticscholar   +1 more source

Computational-Statistical Gaps in Gaussian Single-Index Models

Annual Conference Computational Learning Theory
Single-Index Models are high-dimensional regression problems with planted structure, whereby labels depend on an unknown one-dimensional projection of the input via a generic, non-linear, and potentially non-deterministic transformation.
Alex Damian   +3 more
semanticscholar   +1 more source

Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations

Annual Conference Computational Learning Theory
We study the computational and sample complexity of learning a target function $f_*:\mathbb{R}^d\to\mathbb{R}$ with additive structure, that is, $f_*(x) = \frac{1}{\sqrt{M}}\sum_{m=1}^M f_m(\langle x, v_m\rangle)$, where $f_1,f_2,...,f_M:\mathbb{R}\to ...
Kazusato Oko   +3 more
semanticscholar   +1 more source

On the Sample Complexity of the Linear Quadratic Regulator

Foundations of Computational Mathematics, 2017
This paper addresses the optimal control problem known as the linear quadratic regulator in the case when the dynamics are unknown. We propose a multistage procedure, called Coarse-ID control, that estimates a model from a few experimental trials ...
Sarah Dean   +4 more
semanticscholar   +1 more source

Randomized Complexity of Mean Computation and the Adaption Problem

Journal of Complexity
Recently the adaption problem of Information-Based Complexity (IBC) for linear problems in the randomized setting was solved in Heinrich (J. Complexity 82, 2024, 101821). Several papers treating further aspects of this problem followed.
S. Heinrich
semanticscholar   +1 more source

Current treatment and recent progress in gastric cancer

Ca-A Cancer Journal for Clinicians, 2021
Smita S Joshi, Brian D Badgwell
exaly  

A Complexity Trichotomy for k-Regular Asymmetric Spin Systems Using Number Theory

Computational Complexity, 2023
Jin-Yi Cai   +3 more
semanticscholar   +1 more source

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